United States Customs and Border Protection – AI Use Cases

Use Case Name: AI for Autonomous Situational Awareness 

Use Case ID: DHS-P2 

Use Case Summary: The AI for Autonomous Situational Awareness System is intended to use Internet of Things IoT sensor kits to covertly detect and track illicit cross-border traffic in remote locations.  The system will leverage a motion image/video system enhanced with Artificial Intelligence that is capable of vehicle detection and direction determination. It will also incorporate a motion sensor that, when triggered, wakes up a high-resolution camera to capture a series of pictures, with additional sensors providing confirmation prior to camera capture. Images captured will be processed by Artificial Intelligence models to classify objects, determine vehicle direction at intersections, and provide imagery sufficient for re-identification. Ultimately, the system is intended to create a low footprint, low cost, low power system to provide situational awareness and covert detection., detection and identification of objects at or near the U.S. border, and possibly classification. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Vessel Detection  

Use Case ID: DHS-38  

Use Case Summary: Integrated technologies and analytics enhance maritime detection and the sensor network. Machine-assisted and AI-enhanced detection and tracking allow for improved illicit vessel detection in areas with high volumes of legitimate trade and recreational water vessel traffic by increasing situational awareness and responsiveness to threats.  Vessel Detection allows an agent to set a search area with criteria (e.g., people, drones, vehicles) and transmit those criteria to the sensors.  Images detected by the sensors are automatically recognized using Artificial Intelligence. The AI algorithms filter, detect, and recognize objects, dividing them into Items of Interest (IoI) and other objects.  Detections of IoI are shared with other detection systems while detections of other objects (e.g., animals) are not shared. IoIs can be tracked and maintained across multiple sensors seamlessly.  

Use Case Topic Area:  Law & Justice 

Deployment Status:  Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No  

Use Case Name: Commodity Detection Model (Cargo Insights Team) 

Use Case ID: DHS-69 

Use Case Summary: This project leverages computer vision with object detection and a neural network to analyze X-Ray images and predict the commodity code of detected objects. It analyzes X-Ray images and predicts the commodity code of detected objects, reducing the need for users to manually enter codes for all commodities presented. The model provides a commodity code prediction label with bounding boxes on the image. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Cargo Entity Risk Model 

Use Case ID: DHS-95 

Use Case Summary: The project leverages an ensemble of supervised machine learning models that identifies risk of trade entities likely to have a seizure/violation.  These models are based on aggregated trade entity profiles as well as associative characteristics used to inform risk across  all cargo enforcement risk domains and cargo predictive threat models. The Cargo Entity Risk model/tool enhances cargo predictive threat models by providing a comprehensive risk profile that aggregates historical trade entity transactions, trading partner relationships, reviews, examinations, and violations (within CBP data holdings) to create quantifiable risk measures for all trade entities. The resulting risk measures can be utilized by larger AI/ML cargo risk targeting models to better assess cargo threats. The output of the Cargo Entity Risk (CER) model/tool is a calculated risk measure that supports standardization of trade entity risk for enhanced data and feature development for use in larger mode, or threat-specific cargo predictive risk models. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Automated Data Annotation 

Use Case ID: DHS-165 

Use Case Summary: The Automated Data Annotation system simplifies and enhances data annotation for machine learning by providing tools to efficiently label datasets across various formats, such as images, text, and videos. It supports both manual labeling with an intuitive web interface and automated labeling powered by machine learning to accelerate the process. Human annotation is offered to verify and validate the automated annotations. The intended purpose of the AI is to generate domain specific training data to facilitate model training for specific mission use cases. The expected benefit is increased accuracy and confidence in model development and high-quality, labeled datasets in JavaScript Object Notation (JSON) format ready for machine learning. It also provides metadata, including annotation metrics and quality insights, to ensure accuracy and support model training workflows. 

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Public Information Compilation for Travel Threat Analysis (Dataminr) 

Use Case ID: DHS-183 

Use Case Summary: CBP uses Dataminr, a commercially available open-source alerting tool, which compiles publicly available information to provide alerts for possible threats related to national security, border violence, CBP facilities, CBP employee safety, and other topics with a CBP-nexus involving air, sea, and land travel to and/or from the U.S.  This tool significantly reduces the amount of time it takes for users to collect and compile this data.  CBP manually enters parameters related to these topics into Dataminr.  The results provide a summary of complied information, citation to information sources, and the possible threat (e.g., facility disruption, border violence, natural disaster, or terrorism).  CBP employees review these results, including the source information, to further research the information to determine if there is a possible threat.  

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Acquisition and/or Development) 

Safety- and/or rights-impacting? No.  It was presumed safety-impacting relating to detecting weapons or violence, but the DHS Chief AI Officer determined this use case does not satisfy the definition of safety-impacting AI in M-24-10.  For this use case, the AI output is compiled publicly available information for awareness.  No decisions or actions come directly from the information presented by Dataminr. CBP employees further research the information, including reading the source information, to determine if there is a possible threat and then create an appropriate response or notification based on that research. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No

Use Case Name: AI Enabled Autonomous Underwater Vehicle 

Use Case ID: DHS-194 

Use Case Summary: Advanced sonar, navigation, and communications system subsea vehicle is a fully integrated, hand-portable, low detection threshold system that has the small footprint and maneuverability to inspect underwater infrastructure.  It integrates Doppler Velocity Log (DVL), Ultra-Short Baseline (USBL), Inertial Navigation System (INS), and acoustic and optical modems. This enables highly reliable, fully autonomous underwater missions and provides obstacle detection and collision avoidance.  The system will be developed to assist in the detection of parasitic smuggling attempts on the outer hull of maritime vessels. Office of Field Operations (OFO) has identified significant potential for smuggling of narcotics attached to the outer hull of marine vessels entering and exiting ports of entry. The current identification method is using dive teams or borrowing larger Remotely Operated Vehicle (ROV) units from Local, State, or Federal partners. Through autonomous systems, OFO can more efficiently and safely identify anomalies/items of interest.  The technology allows for increased shared situational awareness in real time for OFO and strategic partners and improves mission planning and agent and officer safety, while reducing reactionary gaps. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Relocatable Multi-Sensor System 

Use Case ID: DHS-234 

Use Case Summary: MDF correlates sensor data of different types into an integrated operational picture, allowing the user to see simplified, single entity tracks in highly complex scenarios.  The system prioritizes items of interest (IOI) automatically based upon user intent and automatically cues sensors.  MDF also classifies detections into groups it is trained for, including aircraft, humans, and vehicles.  This does not include any nexus to biometric detection or image processing. The system uses advanced sensor technology to differentiate valid IOI, such as unmanned aircraft systems and humans, from other detections such as animals or environmental objects. By integrating radar and other sensor data, the system filters out false alarms, ensuring more accurate identification of potential IOI. This capability enhances CBP’s ability to focus on legitimate risks while minimizing the time spent on non-threatening activities, improving operational efficiency at border and security checkpoints. The outputs include real-time data identifying and categorizing potential IOI while filtering out false or non-relevant IOI like animals. These outputs are used to provide situational awareness and support decision-making for CBP personnel. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Integrated Defense and Security Solutions (IDSS) 

Use Case ID: DHS-311 

Use Case Summary: CBP employs computed tomography x-ray systems with automated recognition technology for the inline screening of high-volume parcels to detect contraband. The system integrates AI-driven analytics into non-intrusive inspection systems, enhancing screening efficiency and accuracy by identifying anomalies for CBP personnel to review and, if necessary, conduct additional screening. The systems improve the screening efficiency and accuracy of contraband detection in international express consignment and mail inspection. The system provides a segmented image, highlighting anomalies for further inspection by CBP personnel. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Anomaly Detection in Non-Intrusive Inspection 

Use Case ID: DHS-312 

Use Case Summary: CBP intends to procure, develop, and implement solutions that leverage advanced algorithms and machine learning to analyze data to assist CBP personnel in automating analysis of non-intrusive inspection (NII) images used in cargo and vehicle inspections. The model will identify irregularities or deviations from expected patterns that may indicate concealed contraband or threats by displaying specific areas within scanned images that show anomalies, that possibly needing further screening. It is expected to reduce overall review time. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Acquisition and/or Development)

Safety- and/or rights-impacting? No 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Advanced Analytics for X-ray Images (AAXI) 

Use Case ID: DHS-313 

Use Case Summary: Advanced Analytics for X-ray Images (AAXI) aims to address the problem of anomaly detection in empty commercial vehicles entering the U.S. at land border ports of entry. The AI models achieve this goal by encoding past x-ray images of vehicular border crossings in a semantically meaningful way and comparing the current crossing to detect differences amongst the images to identify anomalies. The system produces bounding boxes around an anomaly or unidentifiable object(s) within an image or any portion of the image that cannot be identified or explained. Benefits include enhancement of the capability of humans to consistently detect items of interest/concern present (and possibly concealed) in vehicles crossing into the United States, and increased clearance rate at border crossings so that vehicles operating safely and lawfully may pass through the border faster. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Acquisition and/or Development) 

Safety- and/or rights-impacting? Yes. Rights-impacting. Before this AI use case is deployed, it will comply with risk management practices for deployed safety impacting AI. Read [LINK to FAQ] about compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Advance RPM Maintenance Operating Reporter (ARMOR) 

Use Case ID: DHS-314 

Use Case Summary: Utilizing AI and physical modeling, the Advance Radiation Portal Monitor (RPM) Maintenance Operating Reporter (ARMOR) project provides predictive maintenance of RPMs, detecting issues with the equipment before the issue causes the screening lane to be inoperable. The system will provide a listing of malfunctioning RPMs categorized by issue severity and predicted date of failure, which will be used to create service tickets. ARMOR will shorten time to service/repair/maintenance of RPMs by two weeks. ARMOR will allow better distribution of resources (travel, spare parts, etc.) with a potential cost decrease of 25-50%. Through decreased outage time, and prediction of equipment degradation, ARMOR will increase radiological/nuclear (R/N) security on U.S. borders.  

Use Case Topic Area: Mission-Enabling (internal agency support)] 

Deployment Status: Pre-deployment (Acquisition and/or Development) 

Safety- and/or rights-impacting? Yes. Safety-impacting. Before this AI use case is deployed, it will comply with risk management practices for deployed safety impacting AI. Read [LINK to FAQ] about compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: RAPTOR (Rapid Tactical Operations Reconnaissance) 

Use Case ID: DHS-317 

Use Case Summary: Rapid Tactical Operations Reconnaissance (RAPTOR) provides real-time surveillance and reconnaissance capabilities to enhance border security by integrating advanced technologies, such as radar, infrared sensors, and video surveillance, to detect and track suspicious activities along U.S. borders. This use case involves testing the capabilities of a vessel hull reader with AI capabilities that produces a test transcription of vessel registration/documentation data and photographs of the vessel. This system will significantly increase domain awareness, the agency’s ability to engage in intelligence-driven operations and enhance officer safety and capabilities to meet operational mission requirements. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation)   

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: AI to Generate Testable Synthetic Data 

Use Case ID: DHS-2362 

Use Case Summary: The Automated Commercial Environment (ACE) is the system the trade community reports imports and exports, and the government determines admissibility. This system is developed and maintained by the Cargo Systems Program Directorate (CSPD) within the Office of Information Technology (OIT) in Customs and Border Protection (CBP). ACE is a large system consisting of hundreds of applications with new capabilities added regularly. CSPD is seeking to incorporate AI to generate more realistic synthetic data without Personally Identifiable Information (PII) for trade partners to utilize in testing new data formats and APIs before releasing new ACE capabilities.  By using synthetic data, the system does not risk any PII spillages. Currently, there are many data issues where test data does not accurately reflect real production data, which results in unrealistic failures when testing and wasted time and resources tracking down false positive errors during testing.  By providing trade partners with more realistic test data, the expectation is that testing times will be shorter and enhancements and capabilities can be delivered quicker., The AI capability would generate test data without PII or other trade sensitive data and allow for more accurate simulation of production data. 

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Anomaly Detection COV Structure 

Use Case ID: DHS-2363 

Use Case Summary: CBP is seeking anomaly detection algorithm (ADA) models that can run on U.S. government systems for rapid screening of passenger and cargo vehicles. The desired end state is a suite of algorithms that supports CBP’s non-intrusive inspection (NII) image analysis for detecting anomalies and interdicting contraband to assist CBP officers’ image review with specific interest on algorithms that facilitate screening for contraband and anomaly detection in passenger vehicles and cargo conveyances. This solution will assist CBP officers in adjudicating large-scale NII x-ray images. The solution will identify regions of interest within the structure of commercially owned vehicles (COVs) and detect anomalies within these regions. It will place bounding boxes around an anomaly or unidentifiable object(s) within an image or any portion of the image that cannot be identified or explained. The algorithm will support the review and analysis conducted by image analysts during NII x-ray image adjudication, ultimately reducing overall review time for NII images.  It is expected that this will enhance the capability of humans to consistently detect items of interest/concern present (and possibly concealed) in vehicles crossing into the United States and increase clearance rate at border crossings, so that vehicles operating safely and lawfully may pass through the border faster.  

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Anomaly Detection Homogenous Cargo 

Use Case ID: DHS-2364 

Use Case Summary: CBP is seeking anomaly detection algorithm (ADA) models that can run on U.S. government systems for rapid screening of passenger and cargo vehicles. The desired end state is a suite of algorithms that supports CBP’s non-intrusive inspection (NII) image analysis for detecting anomalies and interdicting contraband to assist CBP officers’ image review with specific interest on algorithms that facilitate screening for contraband and anomaly detection in passenger vehicles and cargo conveyances. This solution will assist CBP officers in adjudicating large scale NII x-ray images. The solution will identify anomalies within homogenous cargo contained in commercially owned vehicles (COVs). Bounding boxes around an anomaly or unidentifiable object(s) within an image or any portion of the image that cannot be identified or explained. The algorithm will support the review and analysis conducted by CBP image analysts during NII x-ray image adjudication ultimately reducing overall review time for NII images. It is expected that this will enhance the capability of humans to consistently detect items of interest/concern present (and possibly concealed) in vehicles crossing into the United States and increase clearance rate at border crossings, so that vehicles operating safely and lawfully may pass through the border faster.  

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Anomaly Detection POV Structure 

Use Case ID: DHS-2365 

Use Case Summary: CBP is seeking anomaly detection algorithm (ADA) models for rapid screening of passenger and cargo vehicles. The desired end state is a suite of algorithms that supports CBP’s non-intrusive inspection (NII) image analysis for detecting anomalies and interdicting contraband to assist CBP officers’ image review with specific interest on algorithms that facilitate screening for contraband and anomaly detection in passenger vehicles and cargo conveyances. This solution will assist CBP officers in adjudicating large-scale NII x-ray images. The solution will identify regions of interest within the structure of privately owned vehicles (POVs) and detect anomalies within these regions. Bounding boxes around an anomaly or unidentifiable object(s) within an image or any portion of the image that cannot be identified or explained. The algorithm will support the review and analysis conducted by image analysts during NII x-ray image adjudication ultimately reducing overall review time for NII images while facilitating legitimate trade and travel. It is expected that this will enhance the capability of humans to consistently detect items of interest/concern present (and possibly concealed) in vehicles crossing into the United States and increase clearance rate at border crossings, so that vehicles operating safely and lawfully may pass through the border faster. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: CBP Careers Bot – Leo 

Use Case ID: DHS-2366 

Use Case Summary: Visitors to careers.cbp.gov can engage with a decision-tree based chat bot to help access CBP career related information and drive users to take the next action such as contacting a recruiter, attending a career event, or apply for a CBP Career. This bot will be enhanced over the next year to include responses driven by natural language processing (NLP) for predetermined intents. 

Use Case Topic Area: Government Services (includes Benefits and Service Delivery) 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Computer Vision for Aerial Detection of Land and Open Water Items of Interest 

Use Case ID: DHS-2367 

Use Case Summary: Current detection, classification (determining intention and/or threat level of each detection), and tracking of potential, cross-border maritime threats mostly rely on human operators monitoring radar tracks on a screen and scanning the maritime environment with surveillance camera systems.  This capability leverages high fidelity cameras on airborne platforms along with computer vision machine learning (CV/ML) models to automate the detection, classification, and tracking of potential cross-border maritime threats. This capability will automate cross-border maritime threat detection, classification and tracking by providing alerts and tracks of detected/classified maritime threats to system operators, enabling more efficient maritime border security surveillance. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: AI for Software Delivery 

Use Case ID: DHS-2369 

Use Case Summary: The Automated Commercial Environment (ACE) is the system through which the trade community reports imports and exports, and the government determines admissibility. This system is developed and maintained by the Cargo Systems Program Directorate (CSPD) within the Office of Information Technology (OIT) in Customs and Border Protection (CBP). ACE is a large system consisting of hundreds of applications with new capabilities added regularly. CSPD is seeking to incorporate AI into the software delivery process to reduce delivery time as well as increase the quality and security of the ACE system. The initial use case is to integrate AI into the development process to assist developers with code reviews so that when a request to modify code in a baseline is made by a developer AI is integrated into the continuous integration pipeline to examine the code for potential problems and inefficiencies.  The AI model will identify coding errors and recommend fixes as well as make recommendations for improvement and optimization which the request reviewer will assess and determine what, if any, changes need to be made before the code is approved to go into the baseline. By reducing code review time and identifying potential issues earlier in the development CSPD expects to reduce the time to deliver changes and increase initial software quality. 

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Optical Counter – UAS Detection 

Use Case ID: DHS-2371 

Use Case Summary: Current detection, classification [determining intention and/or threat level of each detection], and tracking of potential, cross-border air and ground threats mostly rely on human operators scanning the border environment with surveillance camera systems.  This capability leverages 360-degree rotating, high fidelity cameras on stationary towers along with computer vision machine learning (CV/ML) models to automate the detection, classification, and tracking of potential cross-border air and ground threats. This capability will automate cross-border air and ground threat detection, classification, and tracking, enabling more efficient border surveillance. It will provide alerts and tracks of detected/classified air & ground threats to system operators on a workstation user interface.   

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Thermal Power Generation with Geoseismic IoI Detection and Classification 

Use Case ID: DHS-2375 

Use Case Summary: The Thermal Power Generation and Geoseismic Item of Interest (IoI) detection and classification is able to convert surface heat fluctuations into electrical energy in order to power a seismic sensor. The data generated from the seismic sensor is then paired with a machine learning (ML) algorithm which is able to identify and classify Items of Interest (IoIs), noting the confidence interval that the detected seismic activity is correctly classified. Once an IoI is identified, users will receive alert notifications within their systems and determine the appropriate response in that area. Increases situational awareness in austere environments and reduces need for battery replacement since the devices are self-charging.. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Underwater ROV 

Use Case ID: DHS-2377 

Use Case Summary: The Underwater Remotely Operated Vehicle (ROV) is a submersible drone capable of conducting inspections of maritime vessel hulls to detect underwater threats and contraband. The systems utilize supervised machine learning (ML) to assist in the identification of items of interest on a maritime ship’s hull. Outputs from the system will be the identification of threats and contraband. Users will use the output, an informed decision on if a potential threat or contraband is present on a hull, to determine if additional actions are required, The expected benefit of the system is that users will be able to identify potential threats and contraband on maritime vessels quickly. This identification will allow for the streamlined investigations of a ship’s hull without the need for a dive team. 

Use Case Topic Area: Law & Justice 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Wellness and Physical Fitness Application 

Use Case ID: DHS-2378 

Use Case Summary: The use case helps service members build strength and durability by delivering structured, personalized workout plans to perform at their highest level. Coaches and users can start from a periodized base program built by Tactical Strength and Conditioning (TSAC) certified strength and conditioning specialists to optimize operational readiness — then customize it as much (or as little) as needed. The system will produce personalized physical fitness assessments and programs with real-time AI fitness monitoring and program adjustments, including metrics, graphs, and a display for group and/or individual trends analyses. This will increase user awareness of physical status and associated remedial actions, if necessary, with the ultimate goal of mitigating human capital costs through health and wellness awareness. 

Use Case Topic Area: Health & Medical 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: API Security Vulnerability Technology 

Use Case ID: DHS-2444 

Use Case Summary: Enabling user-access to a secure environment and robust cybersecurity posture is critical to CBP operations. In order to support these objectives, CBP is intending to leverage application programing interface (API) testing technology which machine learning (ML) coupled with natural language processing (NLP) and automated software testing techniques. This platform is intended to automatically scan and continuously monitor APIs to detect potential risks like unauthorized access, data leaks, or weaknesses. Once tests are conducted on APIs, a comprehensive vulnerability report will identify security risks such as broken authentication, exposed data, or misconfigurations. The software is also intended to provide clear remediation guidance based on the applications, environment, data, and tests conducted for end-users, offering step-by-step solutions to fix these vulnerabilities. Additionally, this capability will assign a risk score to help prioritize the most critical issues and ensures APIs comply with industry standards and regulations through detailed compliance checks. With continuous security monitoring, the platform also delivers real-time alerts for new vulnerabilities, empowering teams to maintain robust API security throughout the development and deployment lifecycle. 

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Cyber Threat Detection 

Use Case ID: DHS-2446 

Use Case Summary: Cyber Threat Detection is a cyber platform that enables CBP to detect, engage, and respond to malicious activity across hybrid cloud deployments, protecting both IT and networks. It uses generative AI (GenAI) to create decoys, lures, baits, and breadcrumbs, to detect threats and allows for more proactive threat identification and associated mitigation. The technology will establish a decoy file sharing capability such as SharePoint, Shared Drive, etc. with tailored decoy products or reports and monitor and alert on the access and interactions with the decoys. The technology enables the accurate detection of malicious activity in the cyber environment for actionable insights so that leadership can identify threats and efficiently mitigate them while reducing the cost of other security defenses. With the technology, the user will be alerted of detected compromise, evaluation of the creation of decoys, and the monitoring/analysis of interaction with the decoys from the adversary.  

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Multi-media Insight Tool 

Use Case ID: DHS-2449 

Use Case Summary: The capability will leverage multimodal AI models and a cloud-native application programing interface (API) platform to find similar videos, or to search within videos for objects, spoken language, or sounds through recognition. The platform will provide users the ability to more efficiently search within videos for objects, spoken language, or sounds and the ability to rapidly ingest and extract insights for visual and audio data. With the technology, CBP will be able to more easily track and search for individuals, things, events (such as activated lights/sirens) in video, expanding to searching for an entity or event from one video file across multiple. The technology will integrate multimedia (audio and video) from multiple sources and sensors to generate by-source timelines and provide geospatial reference. With the extracted insights from visual and audio data, users will be able to detect simultaneous events across multiple video files and identify common key events where event times are known, inferring timestamps in linked or subsequent videos. Ultimately, the technology will allow for more efficient investigations. 

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Position Description Generation and Evaluation 

Use Case ID: DHS-2451 

Use Case Summary: Incorporation of large langue models (LLMs) into the position description (PD) classification process, will enable accurate, speedy classification services delivery, increase uniformity in the classification process, and enable more robust PD language, leading to a more accurate assessment and ultimately a better applicant pool and candidate. Accurate PDs will also reduce the risk of PD based litigation or grievance against the agency. The system- created accurate PDs will be verified by Human Resources Specialist while reducing the administrative burden, allowing the agency to accomplish more with less staff. 

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Source Code Development Tool  

Use Case ID: DHS-2452  

Use Case Summary: Current software development usually requires many hours of human coding labor.  This capability accelerates software development by providing a generative artificial intelligence coding assistant.  The coding assistant is based on large language models (LLM) and coding foundation models.  End users may prompt the assistant to code, refine and complete a software project through natural language commands and queries. This capability will enable end users to develop software faster and more efficiently through the use of a generative artificial intelligence (GenAI) coding assistant and which will create functional software code for end users.  

Use Case Topic Area: Mission-Enabling (internal agency support)  

Deployment Status: Pre-deployment (Initiation) 

Safety- and/or rights-impacting? No, use case is too new to fully assess impacts; will be reassessed before end of initiation stage. 

Face Recognition/Face Capture (FR/FC)? No  

Use Case Name: Entity Resolution 

Use Case ID: DHS-24 

Use Case Summary: CBP uses Altana to compile a vast amount of public and lawfully obtained private data regarding cross-board trade. These data elements can include bills of lading, manifests, invoices, and open-source information, as well as elements available only through the Altana subscription. Altana assists in researching supply chain information related to various trade enforcement topics areas such as forced labor and anti-dumping/countervailing duty evasion to better assess trade flow and risk associated with cross-border trade. The data elements provide an illustration for both supply chain and the flow of trade. The AI is used in the background to pull together disparate pieces of information from incompatible data sets to illustrate the supply chains. The illustration is used by the analysts to determine high risk areas for trade targeting in the forced labor mission set. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance) 

Safety- and/or rights-impacting? No. It was presumed safety-impacting relating to trade and export enforcement actions and rights-impacting relating to law enforcement in certain contexts, but the DHS Chief AI Officer determined this use case does not satisfy the definition of either safety-impacting AI or rights-impacting AI in M-24-10. This use case assists by consolidating information from disparate data sources. The AI output is compiled information. Without the use of AI, it is likely the user would experience higher degrees of difficulty searching through multitudes of data elements. The illustration is then used by the analysts to determine high risk areas for trade targeting in the forced labor mission set.  No decisions or actions come directly from the information presented by Altana. CBP employees further research the information, including reading the source information, alongside CBP data holdings to continue researching the probable supply chain before making any recommendations or taking any actions. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.   

Use Case Name: Autonomous Surveillance Tower (AST) 

Use Case ID: DHS-35 

Use Case Summary: The ASTs are lawfully deployed technologies used to support the U.S. Border Patrol mission between Ports of Entry.  ASTs alert when detecting the presence of an IoI that the AI model was trained to detect (i.e., persons, vehicles, animals) in the image frame. When an IoI is detected in monitored areas, the information is sent as a notification to the user interface which generates an audible alert, a pop-up, and highlights the IoI in a green rectangle on the picture or video. A trained CBP agent or user, reviews the image to identify and classify the activity taking place. The AI merely alerts to the presence of an item it was trained to detect. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance)  

Safety- and/or rights-impacting? No.  It was presumed rights-impacting relating to law enforcement in certain contexts, but the DHS Chief AI Officer determined this use case does not satisfy the definition of rights-impacting AI in M-24-10.  The AI in this use case provides alerts when it detects the presence of an IoI (i.e., persons, vehicles, animals) in the image frame.  With regard to persons, this computer vision application is trained to determine if the object in the image frame is a person with a certain of level of confidence and not another object that may be shaped similarly to a person.  After the alert of a detection, a trained agent or user, reviews the image to identify and classify the activity taking place.  The AI merely alerts to the presence of an item it was trained to detect. This is not a biometric system and does not identify or track specific individuals. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.   

Use Case Name: Automated Item of Interest Detection 

Use Case ID: DHS-37 

Use Case Summary: CBP uses software to analyze field imaging in monitored areas and to provide alerts when it detects the presence of an Item of Interest (IoI) that the AI model was trained to detect (i.e., persons, vehicles, animals) in the image frame. The software outputs include a superimposed outline surrounding of the IoI within the image or live feed. Each outline is color-coded based on the degree of certainty that the detection is the item it was trained to detect. The software allows the user to filter based on preferences for detections of IoI. This filtering allows for quick and efficient review and adjudication of the detection(s). After the alert of a detection, a trained CBP agent or user, reviews the image to identify and classify the activity taking place. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance)  

Safety- and/or rights-impacting? No. It was presumed rights-impacting relating to law enforcement in certain contexts, but the DHS Chief AI Officer determined this use case does not satisfy the definition of rights-impacting AI in M-24-10. The AI in this use case runs on video and images captured from lawfully deployed technologies used to support the U.S. Border Patrol mission between Ports of Entry. The AI provides alerts when it detects the presence of an IoI, such as persons, vehicles, animals in the image frame. With regard to persons, this computer vision application is trained to determine if the object in the image frame is a person with a certain of level of confidence and not another object that may be shaped similarly to a person. After the alert of a detection, a trained agent or user, reviews the image to identify and classify the activity taking place. The AI merely alerts to the presence of an item it was trained to detect. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.   

Use Case Name: Aircraft Landing Location Predictor (KESTREL) 

Use Case ID: DHS-65 

Use Case Summary: CBP uses Kestrel in CBP’s Air & Marine Operations Surveillance System (AMOSS) to aid in predicting where an aircraft will likely land based on historical flight paths. After an aircraft radar track has been declared suspect by the officer evaluating the track of interest through other research, Kestrel employs AI/ML to predict where the aircraft is most likely to land. The output results in a display of the top three final locations as displayed on AMOSS using green, yellow, and red lines to depict most to least probable outcomes.   

Use Case Topic Area: Transportation 

Deployment Status: Deployed (Operation and Maintenance)   

Safety- and/or rights-impacting? No. It was presumed rights-impacting relating to law enforcement in certain contexts, but the DHS Chief AI Officer determined this use case does not satisfy the definition of rights-impacting AI in M-24-10. The AI outputs in this use case are used to predict aircraft landing locations and only after the suspect aircraft has already been identified based on the aircraft’s radar track. The output results in a display of the top three final locations using green, yellow, and red lines to depict most to least probable outcomes. These probable outcomes are continually updated and refreshed with up-to-date information and is used for potential contact and reporting purposes after a suspect aircraft has been identified. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.   

Use Case Name: Empty Container Detection Model (Cargo Insights Team) 

Use Case ID: DHS-68 

Use Case Summary: CBP’s Empty Container Detection Model uses machine learning to identify and track empty containers in cargo shipments. By analyzing shipping data and container movements, the model helps detect potential discrepancies, such as empty containers being incorrectly labeled as full, improving the accuracy and efficiency of cargo management and inspections. This enhances border security and optimizes resource allocation for inspections. The model is designed to accurately identify and track empty containers in cargo shipments, preventing errors and fraud in cargo declarations. The AI improves accuracy, enhances efficiency by prioritizing legitimate containers for inspection, and strengthens security by detecting potential smuggling risks. The system applies a prediction label alongside a bounding box on record.  Officers use this information along with all information provided to determine what, if any, further steps are required. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? No 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Passenger Targeting and Vetting 

Use Case ID: DHS-80 

Use Case Summary: The Passenger Targeting and Vetting Model enhances identity verification by comparing traveler data against government records to identify individuals who may require additional scrutiny before travel. The model also analyzes passenger information, such as travel patterns and historical records, to assess risk levels, enabling the prioritization of higher-risk travelers for further inspection by CBP personnel who are always the final decision-makers in the process. This approach enhances both security and operational efficiency by ensuring that resources are focused on the highest-risk individuals, streamlining the overall process of border security.  The AI model assesses traveler data such as travel patterns and historical records, allowing CBP personnel to prioritize higher-risk individuals for further screening. This streamlines the vetting process and allows CBP personnel to focus resources on the most high-risk travelers, thereby improving border security and reducing the burden of manual screening. The outputs are integrated into the Automated Targeting System (ATS), which generates notifications to recommend further inspection or follow-up actions. These recommendations assist CBP personnel in making real-time decisions about which travelers to prioritize for further screening. CBP personnel retain the final authority in the decision-making process, ensuring that human judgment remains central to border security operations. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Passport Anomaly Model (ODIN ESTA) 

Use Case ID: DHS-81 

Use Case Summary: As there is no requirement to notify the U.S. when a country issues a new passport series or an old series expires, Online Document Information Network (ODIN) is an important on-demand passport analysis tool used by officers to identify passport anomalies based on historical passport issuing trends. ODIN is a tool available to CBP officers for confirming the validity of a passport. Should officers send a passport to ODIN for validation, ODIN returns an assessment of passport validity, which includes normal or inconsistent/abnormal passport patterns. This result is used to notify the CBP officer that a passport may require review, as it may be part of a newly released sequence, may be invalid, or even possibly fraudulent. The CBP officer’s review of a passport may involve conducting additional research and scrutiny to determine whether a passport may be a new foreign country sequence, may have been altered, or may even be counterfeit. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance)   

Safety- and/or rights-impacting? No. It was presumed rights-impacting relating to risk assessments regarding immigration, but the DHS Chief AI Officer determined this use case does not satisfy the definition of rights-impacting AI in M-24-10. In this use case, the AI output is an assessment of passport validity in response to an officer’s request for passport validation. This result could be related to an inconsistency or abnormality in a passport’s pattern. This is a tool available to CBP officers for confirming the validity of a passport. This result is used to notify the CBP officer that a passport may require review, as it may be part of a newly released sequence, may be invalid, or even possibly fraudulent. This is only one piece of information provided to CBP Officers during the normal course of their duties. The officers would use any results provided to research the validity of the passport through other sources. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.   

Use Case Name: Agriculture Commodity Model (AGC) 

Use Case ID: DHS-86 

Use Case Summary: Agriculture Programs and Trade Liaisons (APTL) use AGC to leverage statistical sampling and supervised AI/ML models for risk-based inspection of selected agricultural commodities. The AGC Model maximizes CBP’s limited resources by prioritizing inspection of containers deemed high-risk. The AI output is a predicted risk result level for cargo shipments to identify agricultural pest risk. The predicted risk is integrated into the Automated Targeting System (ATS) – Import Cargo and utilized in APTL’s targeting workflow for agriculture pest risk analysis. If a cargo shipment is identified as high-risk for pest infestation, it is prioritized for inspection. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance) 

Safety- and/or rights-impacting? No. It was presumed safety-impacting relating to trade and export enforcement actions, but the DHS Chief AI Officer determined this use case does not satisfy the definition of safety-impacting AI in M-24-10. This use case’s AI output simply provides aggregated information to assist the user in locating relevant information to a research query.  The operator reviews the aggregated information provided on the associated dashboards and determines any next steps. The AI output may be used to produce insights into the overall trade environment, but the output itself is supporting information for CBP personnel and their individual expertise and areas of responsibilities. It does not identify or track individuals. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.   

Use Case Name: HTS Classifier 

Use Case ID: DHS-94 

Use Case Summary: CBP’s HTS Classifier employs AI Natural Language Processing (NLP) and text analytics to analyze product descriptions and predict appropriate Harmonized Tariff Schedule codes. These capabilities align with cargo threat evaluation by integrating unsupervised learning to classify goods efficiently, reducing human error and enhancing compliance. CBP’s HTS Classifier improves trade compliance and enhances cargo risk assessment by streamlining the classification of goods, enabling better integration with machine learning systems, and refining entity risk evaluations. It identifies potential threats linked to specific cargo types and prior violations by categorizing goods based on their descriptions and attributes. These improvements contribute to faster, more accurate classification and risk-based targeting. The HTS Classifier produces outputs that map cargo commodity descriptions to their most probable tariff codes, enhancing classification accuracy. These outputs integrate seamlessly into broader threat-specific risk models, providing features to support predictive risk assessments in cargo security. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? No 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Advanced Trade Analytics Program (ATAP) 

Use Case ID: DHS-101 

Use Case Summary: ATAP uses data analytics, machine learning, and AI to aggregate and analyze vast amounts of historical trade data and current activity data to identify patterns and trends in the trade environment that allow for greater data-driven insights into the threats and opportunities in CBP’s trade mission execution. The output of ATAP’s various analysis is typically provided through data visualizations and dashboards, allowing CBP personnel to examine the information as part of detecting and deterring non-compliance throughout the trade environment. CBP personnel use ATAP to aggregate information, visualize and display activity and patterns, and to assist the user in locating relevant information to a research query.    

Use Case Topic Area: Diplomacy & Trade 

Deployment Status: Deployed (Operation and Maintenance)  

Safety- and/or rights-impacting? No. It was presumed safety-impacting relating to trade and export enforcement actions, but the DHS Chief AI Officer determined this use case does not satisfy the definition of safety-impacting AI in M-24-10. This use case’s AI output simply provides aggregated information to assist the user in locating relevant information to a research query.  The operator reviews the aggregated information provided on the associated dashboards and determines any next steps. The AI output may be used to produce insights into the overall trade environment, but the output itself is supporting information for CBP personnel and their individual expertise and areas of responsibilities. It does not identify or track individuals. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.   

Use Case Name: Non-Intrusive Inspection (NII) 3D Imaging Tool 

Use Case ID: DHS-163 

Use Case Summary: CBP is responsible for the processing of imported mail, which includes, but is not limited to, the examination of commercial and personal parcels to detect contraband while assuring compliance with applicable laws and regulations. CBP uses a 3D imaging tool for border and transportation security. This system generates high resolution, rapid imaging of objects behind occlusions; creates 3D images for existing processes without significant slowdowns; and provides a novel narcotics detection capability for the inspection of packages. The system uses supervised ML-trained algorithms to accelerate identification of anomalies and objects of interest within the output images by CBP officers. Based on the output images, officers are able to triage incoming mail more effectively and make a faster determination of whether to apply additional screening., The solution utilizes AI/ML to generate high resolution, rapid imaging of objects behind occlusions; create 3D images for existing processes without significant slowdowns; and provide a novel narcotics detection capability for the inspection of packages. The system creates detection alerts for Items of Interest. 

Use Case Topic Area: Law & Justice 

Deployment Status: Implementation and Assessment 

Safety- and/or rights-impacting? No 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Babel 

Use Case ID: DHS-185 

Use Case Summary: Babel is a commercially procured tool that helps CBP compile social media and open-source information on travelers who may be subject to further screening for potential violation of laws that CBP is authorized to enforce or administer. The tool searches and aggregates open-source information related to manually entered queries, which CBP can review and utilize to identify potential threats to the United States. CBP uses this tool to conduct targeted queries to aid CBP in open source research to monitor potential threats or dangers, or to identify travelers who may be subject to further inspection for violation of relevant laws . Babel utilizes AI modules for text detection and translation as well as object and image recognition to provide analysts with possible matches to manually review in a single interface, versus doing multiple manual queries. The output is not singly used for action or decision making. Rather, it is used to identify additional open source or social media content for a person or to identify additional selectors (such as phone and emails) that are previously unknown to CBP. These selectors are then compared by an analyst against Government systems to identify any additional derogatory information. These factors often eliminate additional screening for the traveler. 

Use Case Topic Area: Law & Justice 

Deployment Status: Implementation 

Safety- and/or rights-impacting?  Yes. Rights-impacting 

Key Identified Risk & Mitigations: Forthcoming. Office of Management and Budget (OMB) approved a compliance extension through November 30, 2025.   

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Fivecast ONYX 

Use Case ID: DHS-186 

Use Case Summary: Fivecast is a technology platform accessed through an internet-based user interface that provides insight into a variety of social media platforms including, but not limited to, Facebook, Instagram, Telegram, and Twitter.  Fivecast analyzes the strength of connections between social media users and collects both media and activity information from targeted profiles. It also enables the identification of usernames and profiles using individual names, telephone numbers, age, email address, and location.  Fivecast has proven to be one of the most valuable tools in the OSINT technology stack as it enables advanced search, collection, and analysis of publicly available information through a single user interface, facilitating the collection of information regarding people, places, and things across social media platforms, as well as general information held on the surface, deep, and dark web to inform situational awareness. CBP uses Fivecast ONYX to analyze open-source data, including social media and other public platforms, to identify potential threats, monitor illegal activities, and assess risks to national security.  The system enhances CBP’s capability to monitor, analyze, and assess threats related to border security by processing vast amounts of open-source data. CBP aims to detect potential risks, monitor emerging trends, and uncover connections between individuals, organizations, or networks involved in illegal activities such as human trafficking, smuggling, or terrorism, thereby streamlining operations and bolstering security measures.  

Use Case Topic Area: Law & Justice 

Deployment Status: Implementation 

Safety- and/or rights-impacting?  Yes. Rights-impacting 

Key Identified Risk & Mitigations: Forthcoming. Office of Management and Budget (OMB) approved a compliance extension through November 30, 2025.   

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Airship Outpost for Cross Border Conveyance Identification 

Use Case ID: DHS-188 

Use Case Summary: Part of CBP’s mission is the monitoring of cross border activity at and between our nation’s Ports of Entry. This requires maintaining awareness of cross border conveyances such as automobiles, boats, and airplanes. Airship Outpost allows CBP to accurately identify conveyances (aircraft, vessels, automobiles) by ingesting images and then leveraging AI to identify the type of conveyance and to know where to read the alpha numeric values used to identify them (tail number, hull number, license plate). Standards and regulations for the external identification of various types of conveyances vary significantly. For instance, an aircraft tail number, a vessel hull number, and an automobile license plate number. Once a conveyance is identified, the system focuses on the appropriate location to capture the alphanumeric values used for identification. The software then assigns a confidence score to the accuracy of each capture, which is attached to the files transmitted by the array to a database on cross border activity.  AI is solely used to identify the type of conveyance and then document the associated identification number. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance)  

Safety- and/or rights-impacting? No. It was presumed rights-impacting relating to law enforcement in certain contexts, but the DHS Chief AI Officer determined this use case does not satisfy the definition of rights-impacting AI in M-24-10. This use case distinguishes between different types of conveyances and focuses on the appropriate location to capture the alphanumeric values used to identify the conveyance and add to a database on cross border activity. The AI associated with this use case does not produce alerts, or intelligence, related to the alphanumeric values. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.

Use Case Name: Custom Broker License Exam Proctor Support 

Use Case ID: DHS-310 

Use Case Summary: CBP uses AI technology during the remote Customs Broker License Exam (CBLE) to alert exam proctors to activities that may need review (i.e., alerting the proctor when a candidate leaves or when a second person is present). The output of the AI is a box that highlights the examinee’s tile on the proctor’s screen, drawing the proctor’s attention to the examinee’s behavior. Proctors can use the third-party vendor portal to review the alerts.  The examinee’s computer webcam and audio will be used to capture a video and audio recording of the examination by the vendor. After the alert, the proctor reviews the video and audio and determines if there is any potential violation of exam rules. If the proctor determines there is a potential violation, the proctor will create an incident report to describe the concern. Upon request, CBP will have access to the third-party vendor’s audio and video files to review along with any incident report.     

Use Case Topic Area: Education & Workforce 

Deployment Status: Deployed (Operation and Maintenance) 

Safety- and/or rights-impacting? No. It was presumed rights-impacting relating to hiring and employment, but the DHS Chief AI Officer determined this use case does not satisfy the definition of rights-impacting AI in M-24-10. The AI system in this use case doesn’t rely on biometrics of any kind and alerts the proctor to indications of pre-determined activities that may need review.  After the alert, the proctor reviews the video and audio and, based on what the proctor reviews, determines if there is any potential violation of exam rules. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No  

Use Case Name: ERNIE 

Use Case ID: DHS-315 

Use Case Summary: ERNIE is used to analyze Radiation Portal Monitor (RPM) data to enhance the detection of radioactive materials. The system assesses potential threats, improving the accuracy and speed of identifying illicit or hazardous materials, thereby prioritizing high-risk detections, reducing false alarms and ensuring more efficient security and risk management at ports of entry. The model enhances threat detection and prioritizes high-risk targets, improving operational efficiency and national security. The model provides real-time risk assessments and alerts for potential threats detected by the Radiation Portal Monitors. It also provides prioritized recommendations for further screening based on the analysis of radiation data. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? Yes. Safety- and rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: CBP One 

Use Case ID: DHS-381 

Use Case Summary: CBP One is a mobile application developed by CBP to streamline and enhance various border management processes. It allows users, including travelers and border agents, to access multiple CBP services through a single, user-friendly platform. The Traveler Verification System (TVS) is an AI-driven facial recognition technology integrated into CBP One. TVS uses facial recognition to compare live or uploaded images with CBP’s database, enabling real-time identity verification. This automation streamlines border processes, enhances accuracy, and reduces fraud. The system outputs include identity match confirmation, fraud alerts, and traveler status updates for clearance in processes like boarding or border crossing. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting?  Yes. Safety- and rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  Yes. All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone. 

Use Case Name: Unified Processing/Mobile Intake 

Use Case ID: DHS-398 

Use Case Summary: The Unified Processing/Mobile Intake system integrates with the Traveler Verification Service (TVS) to enhance border security operations. The system enables CBP personnel to match detainees’ facial biometrics against CBP’s photo galleries and derogatory image repositories. This process aids in identifying individuals with prior apprehensions and security concerns. The purpose is to facilitate the biometric identification of individuals as they are encountered by CBP for the purpose of expedited processing. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting?  Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  Yes. All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone. 

Use Case Name: Cyber Threat Analysis (Recorded Future) 

Use Case ID: DHS-399 

Use Case Summary: Recorded Future data query enables CBP Cyber Threat Intelligence (CTI) analysts to focus on investigating recently observed relevant cyber threat activity rather than manually identifying, formatting, and searching for such information in multiple locations. Enables these analysts to quickly view known cyber threat activity targeting known vulnerabilities, which will reduce the time to identify risks to the vulnerabilities that exist in CBP’s information technology environment. AI/ML is employed several ways on this platform: For representation of structured knowledge of the world, using ontologies and events; for transforming unstructured text into a language-independent, structured representation, using natural language processing; for classifying events and entities, primarily to help decide if they are important enough to require a human analyst to perform a deeper investigation; to forecast events and entity properties by building predictive models from historic data. This service can also provide cyber risk scorecards for third party vendors, companies, and organizations. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? No 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Vault Access Log (SPVAA) 

Use Case ID: DHS-401 

Use Case Summary: CBP uses the facial recognition technology in Seized Property Vault Activity Automation (SPVAA) to create a log of access to a seized property vault. Photos of the CBP personnel accessing the vault are loaded into the application and the application logs the entrance request, the case number associated with the entrance request, and the individual’s activity in the vault. 

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Deployed (Operation and Maintenance)  

Safety- and/or rights-impacting? No. It was presumed safety-impacting relating to controlling access to government facilities, but the DHS Chief AI Officer determined this use case does not satisfy the definition of safety-impacting AI in M-24-10. This use case provides a record-keeping function, not an access function.  It does not manage or control access to the vault but replaces the manual logbook for logging CBP personnel as they access the associated vault. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? Yes.  All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone.   

Use Case Name: CBP Employee Experience 

Use Case ID: DHS-2373 

Use Case Summary: CBP Office of Human Resources Management leverages Medallia Employee Experience Management Software to ingest, interpret, and operationalize employee survey results and operational data to deliver real time insights related to the experience of USBP recruits, applicants, and employees. Medallia offers Athena AI Text Analytics to analyze qualitative input and layer with quantitative data for holistic experience metrics. These metrics inform HRM leadership of opportunities for process improvement in order to meet congressionally mandated hiring targets and retain a qualified workforce.  
 
CBP HRM has launched the following solutions that leverage Medallia Athena Artificial Intelligence (AI) Text Analytics:  (1)  Digital feedback survey on the public facing CBP Careers Site for visitors interested in a CBP Career to provide feedback on experience finding and applying for a CBP Career. (2) Post-Application Survey and Dashboard – provides opportunity for USBP applicants who receive tentative select to provide feedback on the Careers Site, Application Process, and Recruiter Experience.  (3) Withdraw Survey and Dashboard – provides opportunity for USBP applicants who voluntarily withdraw from the hiring process to provide feedback on their reason for discontinuing and opportunities for future process improvement.  (4) Medical Exam Survey – provides opportunity for USBP applicants who have completed medical exam step to provide feedback on preparation and experience interacting with vendor staff. (5) eQIP Survey – provides opportunity for USBP applicants who have completed eQIP to provide feedback on preparation and experience using the vendor software. (6) Exit Survey – provides opportunity for departing employees to provide feedback on their experience as a CBP employee to inform opportunities for improved retention., To ingest, interpret, and operationalize employee experience data originating from survey results and operational data, Real time insights related to the experience of USBP recruits, applicants, and employees. 

Use Case Topic Area: Mission-Enabling (internal agency support) 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? No 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Passive Body Scanner 

Use Case ID: DHS-2380 

Use Case Summary: Passive Body Scanner’s (PBSs), deployed at various CBP pedestrian border crossings, use an algorithm to identify anomalies in body heat, assisting CBP officers to detect concealed weapons and contraband, allowing for efficient processing of travelers while flagging anomalies for further screening. While the AI provides these recommendations, CBP officers retain the final decision-making authority, reviewing any flagged areas to determine whether additional inspection is necessary. PBS is intended to enhance situational awareness in pedestrian traveler processing to aid CBP officers in observing potentially dangerous objects or contraband in a timely manner pursuant to CBP’s border search authority. This algorithm highlights areas on a person where potential objects may be blocking the subject’s expected body heat and displays these areas on live video image, monitored by a CBP officer. The highlighted areas may show the locations of carried objects, which could be potential weapons or contraband. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? Yes. Rights-impacting 

Key Identified Risks & Mitigations: Forthcoming. Office of Management and Budget (OMB) approved a compliance extension through November 30, 2025.   

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Unmanned Aircraft Collision Avoidance (Skydio) 

Use Case ID: DHS-2383 

Use Case Summary: Skydio X2D Small Unmanned Aircraft System (sUAS) platform operates on video feed only which in turn activates the obstacle avoidance on the unmanned aircraft where the AI capabilities are housed. The obstacle avoidance capability assists the pilot on the ground to avoid colliding the unmanned aircraft with objects such as man-made structures, vehicles, trees, wires, or other objects in the projected flight path. The pilot receives a visual alert on the hand controller, indicating a possible collision and in some cases the aircraft will slow down, change direction to avoid the obstacle, or stop. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance)  

Safety- and/or rights-impacting? No. It was presumed safety-impacting relating to controlling robot movement and autonomous/semi-autonomous vehicles, but the DHS Chief AI Officer determined this use case does not satisfy the definition of safety-impacting AI in M-24-10. The AI output in this use case is not used for the detection of items of interest in support of the border security mission. The AI output only provides collision avoidance for unmanned aircraft by assisting the pilot in avoiding obstacles such as small wires, tree limbs, or other objects. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? No.   

Use Case Name: CBP Translate 

Use Case ID: DHS-2388 

Use Case Summary: CBP Translate is a mobile and web application designed to assist CBP officers in communicating with travelers who speak diverse languages during inspections at U.S. ports of entry. It supports real-time, multilingual translation for interviews, inspections, and other interactions, improving efficiency and accessibility at ports of entry and during border processes., CBP Translate is used to facilitate clear communication between officers and non-English-speaking individuals during border interactions. The AI enhances efficiency by reducing language barriers, supports diverse languages for greater inclusivity, and ensures accurate communication to minimize misunderstandings during critical procedures. The system provides real-time translations of spoken or written communication, detects individuals’ languages for accurate translation, and generates logs of interactions for review. The output is used to support necessary interpretation but sworn statements and official communications for law-enforcement purposes are moved to standard translation services for formal documentation and questioning. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? Yes. Rights-impacting 

Key Identified Risks & Mitigations: Forthcoming. Office of Management and Budget (OMB) approved a compliance extension through November 30, 2025.   

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  No 

Use Case Name: Passenger Counternarcotics 

Use Case ID: DHS-2389 

Use Case Summary: The Passenger Counternarcotics Model uses AI to detect potential narcotics-related threats in passenger baggage, particularly focusing on high-risk indicators. The model is designed to assist CBP personnel in identifying narcotics shipments quickly, ensuring border security and safety. The model enhances the decision-making process of CBP personnel at ports of entry by providing real-time risk assessments related to narcotics smuggling indicators by leveraging data not typically accessible during primary processing, allowing for a rapid and comprehensive evaluation of inbound travelers and vehicles. The benefit is improved detection, enabling personnel to quickly identify high-risk individuals or shipments, which leads to more efficient narcotics interdiction. The output generates risk assessments and recommendations, which are integrated into the primary passenger processing systems, such as the Automated Targeting System (ATS). These notifications provide CBP personnel with actionable insights to identify potential narcotics threats in real-time.  

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Cargo Counternarcotics 

Use Case ID: DHS-2390 

Use Case Summary: The Cargo Counternarcotics Model is integrated within the Automated Targeting System (ATS) and utilizes advanced data analytics and machine learning algorithms to identify and target shipments potentially involved in narcotics smuggling. By analyzing various data sources, including shipping details, historical information, and risk indicators the AI model enhances CBP’s ability to detect and prevent the trafficking of illicit substances and strengthens operational capabilities without compromising the efficiency of cargo processing., AI/ML models identify high risk shipments to aid CBP officers in detecting narcotics smuggling threats, identifying candidate shipments for review and referral for inspection at CBP Ports of Entry (POEs). High-risk model results are returned to users as a system rule hit. These rule hits are viewable in the associated system results window. From this window, CBP operational personnel review and assess result for next action, including possible shipment examination. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Illicit Trade 

Use Case ID: DHS-2391 

Use Case Summary: CBP leverages an advanced AI and machine learning (AI/ML) model to enhance risk assessment in inbound cargo, focusing on critical areas like Intellectual Property Rights (IPR) violations and compliance with the Uyghur Forced Labor Prevention Act (UFLPA). The tools include text analytics and predictive modeling to assist personnel to identify suspicious shipments and flag potential violations of trade laws for further examination. These efforts help CBP prioritize enforcement actions in maritime cargo, targeting counterfeit goods and forced-labor-related imports through data-driven insights. The model identifies high risk shipments to aid CBP personnel in workload associated with detecting threats, identifying candidate shipments for review and referral for further screening. The model analyzes historical data, examination outcomes, and high-risk attributes to identify shipments likely to involve Intellectual Property Rights (IPR) violations or breaches of the Uyghur Forced Labor Prevention Act (UFLPA).  The model results are sent to the Automated Targeting System for review and assessment by operational personnel, who may conduct additional screening if necessary. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting? Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)? No 

Use Case Name: Supervised Traveler Identity Verification Services (Officer Initiated) 

Use Case ID: DHS-2412 

Use Case Summary:  Supervised Traveler Identity Verification Services (Officer Initiated) leverages facial recognition/comparison technology (FR/FC) to confirm the identity of travelers during traditional officer-led processing. In this system, a CBP officer uses FR/FC to compare a traveler’s face to a gallery of stored images from prior government records, such as passports, visas, and previous border crossings. This technology supports officers in validating identities efficiently and accurately while maintaining oversight throughout the verification process. Officers remain responsible for making final determinations based on the results of the FR/FC and their observations, ensuring security and compliance., The TVS Biometric matching service is a cloud-based service that enables CBP to match a passenger’s identity against a trusted source, which improves traveler facilitation and reduces manual identity verification. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting?  Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  Yes. 

All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone. 

Use Case Name: Semi-Supervised Traveler Identity Verification Services (Traveler Initiated) 

Use Case ID: DHS-2413 

Use Case Summary: The Semi-Supervised Traveler Identity Verification Services (Traveler Initiated) leverages biometric facial recognition to streamline identity verification at border crossings. Travelers submit images through self-service kiosks or mobile platforms, which are then compared against government databases, such as previous inspection records and travel documents, for identity confirmation and approval. This system enhances border efficiency and security by expediting processing while ensuring CBP officers maintain oversight to verify matches and address discrepancies. The TVS Biometric matching service is a cloud-based service that enables CBP to match a passenger’s identity against a trusted source, throughout the travel continuum which improves traveler facilitation and reduces manual identity verification. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting?  Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  Yes. All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone. 

Use Case Name: 3^rd Party Traveler Identity Verification Services 

Use Case ID: DHS-2414 

Use Case Summary: 3^rd Party Traveler Identity Verification Services is part of CBP’s Traveler Verification Service (TVS), a biometric system leveraging facial recognition technology (FRT). This system confirms traveler identities at various exit points, including airports, seaports, and land borders, as part of CBP’s Biometric Exit Program.  These services operate under strict privacy guidelines to protect travelers’ personal information, aligning with CBP’s mission of balancing security and convenience., The TVS Biometric Air Exit solution is a cloud-based facial biometric matching service that enables CBP, External Partners, and Other Government Agencies (OGA) to match a passenger’s identity against a trusted source, throughout the travel continuum which improves traveler facilitation and reduces manual identity verification, Leverages DHS facial matching technologies to provide a match or no match response 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting?  Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  Yes. All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone. 

Use Case Name: Mobile Traveler Identity Verification (ESTA Mobile and Mobile Passport Control) 

Use Case ID: DHS-2415 

Use Case Summary: CBP uses facial recognition technology for process efficiency under the Visa Waiver system, using Electronic System for Travel Authorization (ESTA) Mobile, and in identifying arriving travelers at airports of entry, using Mobile Passport Control. ESTA Mobile is an application and screening system used to determine whether citizens and nationals from countries participating in the Visa Waiver Program (VWP) are eligible to travel to the United States. ESTA Mobile extends the functionality to mobile platforms. The ESTA Mobile application captures a live photo from the traveler to perform a liveness test, and permit CBP’s TVS to conduct a 1-to-1 comparison of the traveler’s captured photo against the traveler’s passport e-Chip photo. ESTA mobile app users may either be an applicant, or third-party affiliates may complete an ESTA authorization on behalf of the traveler. If the ESTA Mobile output does not find liveness or cannot determine an identity match, the application can move forward through the ESTA website, simply treating it as filed by a third-party applicant. Mobile Passport Control captures lives photos of a traveler to permit CBP’s TVS to compare the photo to verified identifies compiled in flight galleries. This allows traveler to verify their identity using their mobile device. If a traveler is unsuccessful with mobile passport control, the traveler is simply processed in the regular customs line. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance)  

Safety- and/or rights-impacting? No. It was presumed rights-impacting relating to law enforcement in certain contexts, but the DHS Chief AI Officer determined this use case does not satisfy the definition of rights-impacting AI in M-24-10. For this use case, if the AI output prevents use of the mobile for identity verification, the individual proceeds with the usual process. In the case of a Visa Waiver application, the application moves forward through the ESTA website, simply treating it as filed by a third-party applicant. In the case of Mobile Passport Control, if a match is not returned, the traveler is simply processed in the regular customs line. Read about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? Yes.  All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone. 

Use Case Name: Traveler Identity Verification Services (Vetting) 

Use Case ID: DHS-2416 

Use Case Summary: The Traveler Identity Verification Services (Vetting) uses biometric facial comparison technology to match traveler photographs with existing photographs in CBP’s holdings. These holdings include images captured during prior CBP inspections, U.S. passport and visa records, immigration records, and photographs from DHS encounters. This process is designed to complement the existing biographic vetting processes, enhancing identity verification and ensuring accurate assessments for travel and security purposes. CBP’s Traveler Identity Verification Services (Vetting) utilizes facial recognition technology to enhance threat identification by matching travelers’ biometrics against records of concern. When the system identifies a potential match to concerning records, CBP personnel conduct a manual facial comparison to determine whether the record is likely associated with the individual. 

Use Case Topic Area: Law & Justice 

Deployment Status: Operation and Maintenance 

Safety- and/or rights-impacting?  Yes. Rights-impacting 

Key Identified Risks & Mitigations: This AI system has been tested in operational or real-world environments and risks have been identified and mitigated. Information about risks and mitigations for this use case may be law enforcement sensitive; DHS continues to review details for potential future disclosure in accordance with applicable law and policy. 

Read more about safety and/or rights-impacting AI and compliance with required minimum risk management practices. 

Face Recognition/Face Capture (FR/FC)?  Yes.  All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone. 

Use Case Name: Process Efficiency Traveler Identity for Airline Check-in and Bag Drop 

Use Case ID: DHS-2417 

Use Case Summary: This use case utilizes facial comparison technology, Traveler Verification Service (TVS), for identity verification at check-in or bags drop for air travel.  For bag drop, the Transportation Security Agency (TSA) has an established process under 49 U.S.C. § 114.1 for carriers to request an alternate procedure for identity verification. For these technical demonstrations, CBP’s TVS may serve as the requested alternate procedure. Air carriers, in voluntary partnership with CBP, may purchase camera equipment in order to capture photos at check-in and again at baggage drop for transmission to CBP. The TVS matching service creates a biometric template of each international traveler’s photo and compares it against templates of existing DHS holdings (i.e., U.S. passports, U.S. visas, and/or other DHS encounters) in order to provide identity verification on behalf of the CBP partner.  In the event of a positive match, the TVS returns a unique identifier and matching results to the air carrier, and the traveler may proceed to finish the check-in/bag drop process. The matching result can be used by airlines (1) to meet their CBP regulatory requirement to verify specific passenger information and (2) their TSA regulatory requirement to accurately verify traveler’s identities. This is a voluntary opt-in process efficiency option provided to travelers. 

Use Case Topic Area: Law & Justice 

Deployment Status: Deployed (Operation and Maintenance)   

Safety- and/or rights-impacting? No. It was presumed rights-impacting relating to law enforcement in certain contexts, risk assessments regarding immigration, and biometric identification in public spaces, but the DHS Chief AI Officer determined this use case does not satisfy the definition of rights-impacting AI in M-24-10. This use case provides biometric technology and the use of which is voluntary. If a traveler chooses to use it and the service cannot match a traveler, the traveler may continue check-in/bag drop via another means. CBP does not make any decision or action based on a no-match. Read more about safety and/or rights-impacting AI. 

Face Recognition/Face Capture (FR/FC)? Yes.  All Face Recognition and Face Capture (FR/FC) technology is tested both prior to operational use and at least every three years during operational use. DHS Science and Technology (S&T) oversees testing and evaluation based on International Organization for Standardization/ International Electrotechnical Commission (ISO/IEC) standards and technical guidance issued by National Institute of Standards and Technology (NIST). DHS S&T applies laboratory, scenario, and operational testing to cost-effectively characterize technology performance and, when feasible, disaggregate performance by user demographics such as gender, age, and skin tone. 

Use Case Name: Autonomous Maritime Awareness 

Use Case ID: DHS-P3 

Use Case Summary: The Autonomous Maritime Awareness system combines surveillance towers, ocean data solutions, unmanned autonomous surface vehicles (ASV), and AI to autonomously detect, identify, and track items of interest in a maritime environment. The towers are low-cost, customizable, and relocatable surveillance systems. They are equipped with a suite of radars and day/night camera sensors. The ASVs have been ruggedized for the open ocean and are powered by wind, solar, and/or onboard engine as required, allowing them to operate in an area of responsibility (AOR) for up to 12 months. Their sensor suite includes cameras and radar. Both systems use AI/ML to detect and identify objects, determine items of interest (IoI) and autonomously track those items using their sensor suites. Once identified, these systems can send alerts to monitoring agencies for at-sea interdiction of potential targets and/or intel collections. 

Deployment Status: Inactive (no longer used).  

Use Case Name: Autonomous Aerostat 

Use Case ID: DHS-23

Use Case Summary: Aerostat capability that uses three tethers instead of the traditional single tether, coupled with advanced weather sensors, analytic capabilities, and powerful winches. The AI/ML model is used to detect the need to launch and land based on weather. It also leverages AI and robotics to autonomously launch and recover the aerostat during inclement weather events without the need for on-site staffing, allowing the aerostat to operate autonomously, saving time and manpower.  

Deployment Status:  Inactive (no longer used) 

Use Case Name: Geospatial Imagery Utilizing Annotation 

Use Case ID: DHS-27

Use Case Summary: Leverages a commercial constellation of Synthetic Aperture Radar (SAR) satellites with readily available data, capable of imaging any location on Earth, day, and night, regardless of cloud cover. Utilizes AI, including machine vision, object, detection, object recognition, and annotation to detect airframes, military vehicles, and marine vessels, as well as built-in change detection capabilities for disaster response missions. 

Deployment Status: Inactive (no longer used).  

Use Case Name: Use of Technology to Identify Proof of Life 

Use Case ID: DHS-28

Use Case Summary: Mobile applications rely on product for liveness detection to avoid use of spoofed or fraudulent images by bad actors. Being able to accept submitted data with confidence that the submitting individual is who and where they claim to be is critical to the functionality of the app within the agency environment. 

Deployment Status:  Inactive (consolidated with another use case). This use case was consolidated under CBP One (DHS-381).

Use Case Name: Integrated Digital Environment 

Use Case ID: DHS-29

Use Case Summary: The Integrated Digital Environment provides managers with a better understanding of end user workflows, most and least used applications, and opportunities for improvement. The AI/ML model applies to end user activity data (e.g., use of applications, flow between applications) to help CBP identify opportunities for more efficient or effective configuration of interfaces, use of resources, or development and deployment of CBP’s applications. It tailors analytics and insight generation to allow metrics gathering, usage recording/observation, dashboarding, and workflow experimentations/suggestions to support analysts utilizing the entire suite of agency and open-source data systems. It also customizes existing capabilities to allow the exact automations needed for agency applications and systems, creating an integrated digital environment for greater connectivity and security between applications, and better ability for CBP administrators to manage and optimize use of applications by end users. 

Deployment Status: Inactive (no longer used) 

Use Case Name: AI Curated Synthetic Data 

Use Case ID: DHS-31 

Use Case Summary: AI Curated Synthetic Data creates synthetic data for computer vision to enable more capable and ethical AI when detecting anomalies in complex environments.  Specifically, it creates an emulated X-ray sensor that can produce visually realistic synthetic X-ray scan images similar to real X-ray scan images, and virtual 3D assets of vehicles and narcotics containers. These images will be used to enhance the development of Anomaly Detection Algorithms for Non-Intrusive Inspection (NII), incorporating Artificial Intelligence/Machine Learning (AI/ML) for the detection of narcotics and other contraband in conveyances and cargo. The availability of rare event/outlier data or labeled data that can be used to train and automate detection is severely limited. The technology enhances available libraries of true positives and normal scans from CBP NII systems and supports development of Automated Threat Recognition (ATR) algorithms designed to quickly identify items of interest. Through the technology, the end user will have access to enhance existing, deployed algorithms to increase detection performance. 

Deployment Status: Inactive (research and development only). This use case was reported in a previous version of the DHS AI Use Case Inventory but is a research and development use case that is not planned to be deployed. 

Use Case Name: Data and Entity Resolution 

Use Case ID: DHS-32 

Use Case Summary: Product uses ML modeling to ingest multiple data sources and evolve models that associate disparate records to identify probable entities and/or identify commonalities between multiple independently submitted records. The automation of entity resolution within the models is supported by a tool that enables non-technical end users to continuously train models through a user-friendly interface. 

Deployment Status:  Inactive (no longer used) 

Use Case Name: RVSS Legacy Overhauled System Project (INVNT) 

Use Case ID: DHS-138 

Use Case Summary: Video Computer Aided Detection (VCAD) (also known as Matroid AI) is software that enables CBP end users to create and share vision detectors. VCAD detectors are trained computer vision models that recognize objects, people, and events in any image or video stream. Once a detector is trained, it can monitor streaming video in real time, or efficiently search through pre-recorded video data or images to identify objects, people, and events of interest. Users can view detection information via a variety of reports and alert notifications to process and identify important events and trends. Detection data is also available through VCAD’s powerful developer Application Programming Interface (API) and language specific clients, so CBP applications can be integrated with the power of computer vision. 

Deployment Status:  Inactive (consolidated with another use case). This use case was consolidated under Automated Item of Interest Detection (DHS-37).

Use Case Name: Agent Portable Surveillance 

Use Case ID: DHS-162

Use Case Summary: The agent portable surveillance system is a backpack mobile unit meant for single agent deployments. The system identifies border activities of interest by using AI/ML to analyze data from Electro-Optical/Infra-Red cameras and radar. When an activity is detected, the system sends the information to agents through the Team Awareness Kit (TAK). Detections are shared with CBP TAK users to enhance efficiency and agent/officer safety. 

Deployment Status:  Inactive (no longer used) 

Use Case Name: Open-source News Aggregation 

Use Case ID: DHS-171

Use Case Summary: The platform enables users to make better decisions faster by identifying and forecasting emerging events on a global scale to mitigate risk, recognize threats, greatly enhance indications and warnings, and provide predictive intelligence capabilities. The AI/ML models enable rapid access to automated intelligence assessments by fusing, processing, exploiting and analyzing open sources of data (including news, social media, economic indicators, governance indicators, travel warnings, weather and other sources). This system is an immediate and substantial force multiplier that shifts the traditional approach of monitoring and assessing the operational environment to focus on the forecast of the future geopolitical, socio, and economic environment. 

Deployment Status: Inactive (no longer used) 

Use Case Name: Port of Entry Risk Assessments 

Use Case ID: DHS-343

Use Case Summary: CBP utilizes AI to develop, inform, and augment risk assessment processes that evaluate trade and travel data in real-time.  AI methods are applied to CBP data holdings, and the results are used to inform decision making.  These tools are continuously evaluated to ensure accuracy and precision, and support CBP’s core mission as part of the layered risk assessment strategy. 

Deployment Status: Inactive (no longer used)  

Use Case Name: Traveler Verification Service (TVS) 

Use Case ID: DHS-344

Use Case Summary: The Traveler Verification Service (TVS) provides CBP a biometric entry/exit system to record arrivals and departures to and from the United States. CBP uses TVS as its backend matching service for all biometric entry and exit operations that use Facial Comparison. CBP creates localized photo “galleries” from images captured during previous entry inspections, photographs from U.S. passports and U.S. visas, and photographs from other DHS encounters. The images are converted into templates and the actual photograph is discarded. The templates are securely stored, and are what make up the TVS gallery. The templates are then used by the Facial Comparison system to verify a traveler’s identity when they arrive or depart the U.S. When the traveler presents him or herself for entry, or for exit, the traveler will encounter a camera connected to TVS. This camera matches live images with the existing photo templates from passenger travel documents. Once the camera captures a quality image and the system successfully matches it with historical photo templates of all travelers from the gallery associated with that particular manifest, the traveler proceeds to inspection for admissibility by a CBP Officer, or exits the United States. For more information, please read the DHS/CBP/PIA-056 – Privacy Impact Assessment for the Traveler Verification Service.  

Deployment Status:  Inactive (no longer used).  This use case covered several uses of face recognition/face capture (FR/FC) technology, TVS, and those FR/FC uses have been separated into individual, inventoried use cases such as Supervised Traveler Identity Verification Services (Officer Initiated) (DHS-2414)

Use Case Name: I4 Viewer Matroid Image Analysis 

Use Case ID: DHS-424

Use Case Summary: Matroid is a software that enables CBP end users to create and share vision detectors. Matroid detectors are trained computer vision models that recognize objects, people, and events in any image and in video streams. Once a detector is trained, it can monitor streaming video in real time, or efficiently search through pre-recorded video data or images to identify objects, people, and events of interest. Users can view detection information via a variety of reports and alert notifications to process and identify important events and trends. Detection data is also available through Matroid’s powerful developer Application Programming Interface and language-specific clients, so CBP applications can be integrated with the power of computer vision. 

Deployment Status: Inactive (no longer used)